The Llama 3 models were trained using Meta's Research SuperCluster and production clusters, with the pretraining process utilizing a cumulative 7.7M GPU hours of computation. The models were also evaluated on standard automatic benchmarks using Meta's internal evaluations library. The markdown data also provides instructions on how to use the models with transformers and the original `llama3` codebase. Developers are advised to perform safety testing and tuning tailored to their specific applications of the model before deployment.
Key takeaways:
- The Meta Llama 3 is a large language model developed by Meta, optimized for dialogue use cases and outperforms many of the available open source chat models.
- Llama 3 comes in two sizes — 8B and 70B parameters — in pre-trained and instruction tuned variants, and can run on multiple operating systems.
- The model was trained on over 15 trillion tokens of data from publicly available sources and does not include Meta user data.
- Meta has taken steps to limit misuse and harm, and supports the open source community. Developers are encouraged to perform safety testing and tuning tailored to their specific applications of the model.